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US President Barack Obama speaks in the East Room at the White House in Washington, DC, on April 2, 2013 to announce his Administration’s BRAIN, Brain Research through Advancing Innovative Neurotechnologies, Initiative. Launched with approximately $100 million in the President’s Fiscal Year 2014 Budget, the BRAIN Initiative ultimately aims to help researchers find new ways to treat, cure, and even prevent brain disorders. AFP PHOTO/Jewel Samad (Photo credit: JEWEL SAMAD/AFP/Getty Images)

Mental and neurological disorders cost the U.S. economy more than $1.5 trillion a year according to a 2016 report from the Information Technology & Innovation Foundation. From epilepsy, Alzheimer’s and Parkinson’s disease to autism, schizophrenia, depression and even traumatic brain injury, brain disorders take a toll on our society.

Inscopix's brain imaging technology, nVista, is both a hardware and software platform made up of a tiny miniature microscope (smaller than your fingertip) and a data analysis package. The tiny microscope gives scientists the ability to have a real-time view of activity from a large group of neurons (1,200) in the brain region associated with learning and memory. The platform gives scientists the ability to record how neurons fire up and in what sequence which will give insight into understanding how the brain works when we're healthy and how it malfunctions in disease.

"Neuroscience has made significant strides in understanding the anatomical brain, but has lacked access to the game-changing technologies that provide deep insights into the active, functional brain at the level of neural circuits," said Kunal Ghosh, CEO and co-founder, Inscopix. "But now, by having the technology to literally peer into the thinking, working brain and to be able to study the neural circuits of freely behaving subjects, we have the tools to understand brain function and therefore also brain dysfunction in real time. This is key to understanding how the brain works and to understanding brain disease."

Ghosh says to think of it in the context of an orchestra.

"Historically neuroscientists have been listening to one instrument at a time - and when you do that it’s hard to deduce that you’re listening to Beethoven’s 5th. But if you learn how to discriminate the individual instruments you’re hearing, eventually the picture becomes clearer," adds Ghosh. "It’s this more holistic picture we’re after. We want to know what are the instruments - cell types in this instance - are within the context of an actual symphony, i.e. real behavior."

Take facial recognition as a real-life example. The human brain performs this function easily and with low energy. A computer on the other hand can recognize and tag faces faster than the human brain, but it requires a lot more energy and is prone to errors because of non controllable conditions like lighting or shadow. Ghosh says that by understanding how the brain performs facial recognition, we could modify algorithms so computers can achieve this outcome more accurately, faster but with lower energy consumption than what's possible today.

Ghosh believes that decoding the underlying intelligence in the active brain, we'll be able to discover advanced algorithms to support and evolve artificial intelligence and machine learning.